Improved approach to the solution of inverse kinematics problems for robot manipulators
| dc.contributor.author | Karlik B. | |
| dc.contributor.author | Aydin S. | |
| dc.date.accessioned | 2025-04-10T11:18:18Z | |
| dc.date.available | 2025-04-10T11:18:18Z | |
| dc.date.issued | 2000 | |
| dc.description.abstract | A structured artificial neural-network (ANN) approach has been proposed here to control the motion of a robot manipulator. Many neural-network models use threshold units with sigmoid transfer functions and gradient descent-type learning rules. The learning equations used are those of the backpropagation algorithm. In this work, the solution of the kinematics of a six-degrees-of-freedom robot manipulator is implemented by using ANN. Work has been undertaken to find the best ANN configurations for this problem. Both the placement and orientation angles of a robot manipulator are used to fin the inverse kinematics solutions. | |
| dc.identifier.DOI-ID | 10.1016/S0952-1976(99)00050-0 | |
| dc.identifier.uri | http://hdl.handle.net/20.500.14701/53365 | |
| dc.publisher | Elsevier Science Ltd | |
| dc.title | Improved approach to the solution of inverse kinematics problems for robot manipulators | |
| dc.type | Article |